Adaptive computation offloading policy for multi-access edge computing in heterogeneous wireless networks
H Ke, H Wang, W Sun, H Sun - IEEE Transactions on Network …, 2021 - ieeexplore.ieee.org
In heterogeneous wireless networks, massive mobile terminals randomly generate a large
number of computation tasks (payloads). How to better manage these mobile terminals …
number of computation tasks (payloads). How to better manage these mobile terminals …
Unmanned-aerial-vehicle-assisted computation offloading for mobile edge computing based on deep reinforcement learning
H Wang, H Ke, W Sun - IEEE Access, 2020 - ieeexplore.ieee.org
Users in heterogeneous wireless networks may generate massive amounts of data that are
delay-sensitive or require computation-intensive processing. Owing to computation ability …
delay-sensitive or require computation-intensive processing. Owing to computation ability …
Optimization for computational offloading in multi-access edge computing: A deep reinforcement learning scheme
J Wang, H Ke, X Liu, H Wang - Computer Networks, 2022 - Elsevier
Owing to their limited computing power and battery level, wireless users (WUs) can hardly
handle compute-intensive workflows by the local processor. Multi-access edge computing …
handle compute-intensive workflows by the local processor. Multi-access edge computing …
Decentralized computation offloading for multi-user mobile edge computing: A deep reinforcement learning approach
Z Chen, X Wang - EURASIP Journal on Wireless Communications and …, 2020 - Springer
Mobile edge computing (MEC) emerges recently as a promising solution to relieve resource-
limited mobile devices from computation-intensive tasks, which enables devices to offload …
limited mobile devices from computation-intensive tasks, which enables devices to offload …
Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning
To improve the quality of computation experience for mobile devices, mobile-edge
computing (MEC) is a promising paradigm by providing computing capabilities in close …
computing (MEC) is a promising paradigm by providing computing capabilities in close …
Multi-agent deep reinforcement learning-based partial task offloading and resource allocation in edge computing environment
H Ke, H Wang, H Sun - Electronics, 2022 - mdpi.com
In the dense data communication environment of 5G wireless networks, with the dramatic
increase in the amount of request computation tasks generated by intelligent wireless …
increase in the amount of request computation tasks generated by intelligent wireless …
Computation offloading in beyond 5G networks: A distributed learning framework and applications
Facing the trend of merging wireless communications and multi-access edge computing
(MEC), this article studies computation offloading in beyond fifth generation networks. To …
(MEC), this article studies computation offloading in beyond fifth generation networks. To …
Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …
architecture, which can empower user equipments (UEs) with computation and energy …
A deep reinforcement learning approach for collaborative mobile edge computing
J Wu, H Lin, H Liu, L Gao - ICC 2022-IEEE International …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising approach to reduce the network traffic load
and alleviate the back-haul congestion by pushing computation down to the network edge …
and alleviate the back-haul congestion by pushing computation down to the network edge …
Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing
Mobile edge computing can effectively reduce service latency and improve service quality
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …